An artificial intelligence framework and its bias for brain tumor segmentation: A narrative review
Background Artificial intelligence (AI) has become a prominent technique for medical
diagnosis and represents an essential role in detecting brain tumors. Although AI-based …
diagnosis and represents an essential role in detecting brain tumors. Although AI-based …
Imaging cardiovascular calcification
Y Wang, MT Osborne, B Tung, M Li… - Journal of the American …, 2018 - Am Heart Assoc
Cardiovascular disease is the leading cause of morbidity and mortality worldwide.
Atherosclerosis is a complex and multifactorial process, characterized by early …
Atherosclerosis is a complex and multifactorial process, characterized by early …
A novel block imaging technique using nine artificial intelligence models for COVID-19 disease classification, characterization and severity measurement in lung …
Computer Tomography (CT) is currently being adapted for visualization of COVID-19 lung
damage. Manual classification and characterization of COVID-19 may be biased depending …
damage. Manual classification and characterization of COVID-19 may be biased depending …
Plaque tissue morphology-based stroke risk stratification using carotid ultrasound: a polling-based PCA learning paradigm
This chapter introduces a polling-based principal component analysis strategy embedded in
the machine-learning framework to select and retain dominant features, resulting in superior …
the machine-learning framework to select and retain dominant features, resulting in superior …
Stroke risk stratification and its validation using ultrasonic echolucent carotid wall plaque morphology: a machine learning paradigm
Stroke risk stratification based on grayscale morphology of the ultrasound carotid wall has
recently been shown to have a promise in classification of high risk versus low risk plaque or …
recently been shown to have a promise in classification of high risk versus low risk plaque or …
Calcium detection, its quantification, and grayscale morphology-based risk stratification using machine learning in multimodality big data coronary and carotid scans: a …
Purpose of review Atherosclerosis is the leading cause of cardiovascular disease (CVD) and
stroke. Typically, atherosclerotic calcium is found during the mature stage of the …
stroke. Typically, atherosclerotic calcium is found during the mature stage of the …
Wall-based measurement features provides an improved IVUS coronary artery risk assessment when fused with plaque texture-based features during machine …
Background Planning of percutaneous interventional procedures involves a pre-screening
and risk stratification of the coronary artery disease. Current screening tools use stand-alone …
and risk stratification of the coronary artery disease. Current screening tools use stand-alone …
[HTML][HTML] Intra-and inter-operator reproducibility of automated cloud-based carotid lumen diameter ultrasound measurement
Background Common carotid artery lumen diameter (LD) ultrasound measurement systems
are either manual or semi-automated and lack reproducibility and variability studies. This …
are either manual or semi-automated and lack reproducibility and variability studies. This …
Diagnostic tests for vascular calcification
Vascular calcification (VC) is the heterogeneous endpoint of multiple vascular insults, which
varies by arterial bed, the layer of the arterial wall affected, and is propagated by diverse …
varies by arterial bed, the layer of the arterial wall affected, and is propagated by diverse …
Deep learning paradigm and its bias for coronary artery wall segmentation in intravascular ultrasound scans: a closer look
Background and Motivation: Coronary artery disease (CAD) has the highest mortality rate;
therefore, its diagnosis is vital. Intravascular ultrasound (IVUS) is a high-resolution imaging …
therefore, its diagnosis is vital. Intravascular ultrasound (IVUS) is a high-resolution imaging …